content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_celsius(temperature_in_fahrenheit):
"""
Returns the temperature in Celsius of the given Fahrenheit temperature.
For example, this function returns XXX when given YYY.
Type hints:
:type temperature_in_fahrenheit: float
"""
return (temperature_in_fahrenheit - 32) * (5 / 9) | 501b5c3c6c7fe9792fd12cabbae71eddfbc34f58 | 46,644 |
def solve_f35d900a(x):
"""
Difficulty: High
The Problem: The input grid is a rectangular (list of lists) matrix with variable shape, with numbers ranging
from 0 to 9. (inclusive). Different colors of the color spectrum are represented by the integers.
The task is to identi... | da779b86563f684b6e8b00c7f229a0985e504e40 | 46,645 |
def config_fixture(hass):
"""Define a config entry data fixture."""
return {
CONF_USERNAME: "user@email.com",
CONF_PASSWORD: "password",
} | 7c14083c8254f367ec93e1b5e111f0502969b59a | 46,646 |
import scipy
def erfc(x):
"""
Complimentary error function, with handling of Quantity objects
Only Dimensionless quantities can be handled
erfc(x) = 1 - erf(x)
"""
if isinstance(x, Quantity):
return scipy.special.erfc(x.to("").magnitude)
else:
return scipy.special.erfc(x) | a5cb49b658252227b9b3fcd34ec8107bd399545d | 46,647 |
import bz2
import json
import codecs
def json_exporter(data, filepath, compress=True):
"""Export a file to JSON. Compressed with ``bz2`` is ``compress``.
Returns the filepath of the JSON file. Returned filepath is not necessarily ``filepath``, if ``compress`` is ``True``."""
if compress:
filepath... | dcdb9026b302c3bec6b6a7215cee0498a8655a61 | 46,649 |
def is_linear(x, y):
"""
Returns True if molecule is linear
(largest eigenvalue almost equivalent to second largest)
"""
x = x - np.mean(x, axis=0)
y = y - np.mean(y, axis=0)
L, Q = sorted_eigh(build_F(x, y))
if L[0]/L[1] < 1.01 and L[0]/L[1] > 0.0:
return True
else:
... | e1316292474a23b9ee04bafac47c08ed47b02b43 | 46,650 |
import math
def _realroots_quadratic(a1, a0):
"""gives the real roots of x**2 + a1 * x + a0 = 0"""
D = a1*a1 - 4*a0
if D < 0:
return []
SD = math.sqrt(D)
return [0.5 * (-a1 + SD), 0.5 * (-a1 - SD)] | ad61307a09b9f5cbf444f0bd75448b39b09b2e96 | 46,651 |
def add_column(recarray, name, val, index=None):
#Stolen from Ska.Numpy
"""
Add a column ``name`` with value ``val`` to ``recarray`` and return a new
record array.
:param recarray: Input record array
:param name: Name of the new column
:param val: Value of the new column (np.array or list)
... | 92f05bfe58da4c1b37a9309d7aff624d422e2163 | 46,652 |
def gunning_fog_index(n_words, n_polysyllable_words, n_sents):
"""https://en.wikipedia.org/wiki/Gunning_fog_index"""
return 0.4 * ((n_words / n_sents) + 100 * (n_polysyllable_words / n_words)) | aeb295edfa563027952f6a934636487e04b2b266 | 46,653 |
import imageio
def makeGIF(FF_input, start_frame=0, end_frame =255, ff_dir = '.', deinterlace = True, print_name = True, optimize = True, Flat_frame = None, Flat_frame_scalar = None, dark_frame = None, gif_name_parse = None, repeat = True, fps = 25, minv = None, gamma = None, maxv = None, perfield = False, data_type=... | 077d238fac7fe9861eba05ff2128266a1ac4ad80 | 46,654 |
def russell_rao(
x: BinaryFeatureVector, y: BinaryFeatureVector, mask: BinaryFeatureVector = None
) -> float:
"""Russel-Rao similarity
Russell, P. F., & Rao, T. R. (1940).
On habitat and association of species of anopheline larvae in south-eastern Madras.
Journal of the Malaria Institute of India, ... | 6d5be97809f94bb217f60f5490c0accbb2dda76e | 46,655 |
def _generate_windows_body(hooks):
"""Generate Windows specific functions.
At the moment it implements load_impls_from_library, class destructor, and an utility function
to convert from utf8 to wide-strings so we can use the wide family of windows
functions that accept unicode.
"""
# generate d... | 27597f8556cdb4383179245a423a45a72324e2ae | 46,656 |
def get_binary(img_gray):
"""
Get binary threshold filter of image.
"""
thresh = cv2.threshold(img_gray, 128, 255, cv2.THRESH_BINARY)[1]
thresh = thresh[:, :, np.newaxis]
return thresh | 4353d807fc5d015a772ee138e358be3d24d1cba7 | 46,657 |
def bt_rr(weights, bounds):
"""
LP-based OBBT using ReLU relaxation. The procedure is named RR in the paper.
Assuming that NN model has K-1 hidden layers with ReLU activation and 1 linear output layer
Variables are named as x_i_j, where i is the layer number, and j is the unit number (of layer i)
... | 675abbd09569e70ee313ae430f0fe4e896c8537c | 46,658 |
def energy(sig: _Array) -> _Array:
"""Total energy of time domain signal.
Args:
sig: Time domain signal.
Returns:
Energy along fist axis.
"""
if not _np.isfinite(sig).all():
raise ValueError('Input ``sig`` contains NaNs or infinite values.')
return _np.sum(_np.square(_... | b102bf559e8c087f8fe2125c3e319dd1438b227f | 46,659 |
def _compute_expected_shocks(dense_key_to_choice_set_in_period, optim_paras):
"""Compute an array with the expected value of the shocks."""
n_wages = len(optim_paras["choices_w_wage"])
exp_shocks = np.zeros(len(optim_paras["choices"]))
var = np.diag(optim_paras["shocks_cholesky"].dot(optim_paras["shock... | b270b1507f930a4e91ac1dbc5fe61013f9f7ad53 | 46,660 |
import logging
def a_star(graph, start, goal):
""" this thing does not work :( """
# pdb.set_trace()
logger.setLevel(logging.INFO)
queue = [ [start] ]
step = 0
logging.info("START: %s" % start)
logging.info("GOAL: %s" % goal)
def a_star_sort(path1, path2):
l1 = path_length... | b0ffc567845c1c0ba15d6a7c1848af67de5e1230 | 46,661 |
def _preprocessor_public(X_raw):
"""Data preprocessing function.
This function prepares the features of the data for training,
evaluation, and prediction.
Parameters
----------
X_raw : ndarray
An array, this is the raw data as downloaded
Returns
... | 58ddca1808edffcd0020feb46735ff6302f56df7 | 46,662 |
def alreadyHasEntry(oldClassString, og):
""" Return true if there is already an owl:Class with the old id"""
namespace = oldClassString.split(':')[0]
if namespace == 'http':
target = rdflib.URIRef(oldClassString)
print('OLD CLASS ID IS A URL', oldClassString)
else:
try:
... | 482dbd7c62bff21dae9b9c563ca86fb9b5fab560 | 46,663 |
def loadTLE(tle_file, satlst=None):
""" load TLE from file """
with open(tle_file, 'r') as f:
satlist = []
for l1 in f:
l2 = f.readline()
l3 = f.readline()
norad_id = l2[2:8]
if satlst is not None:
if norad_id in satlst:
... | 1c33f3673a25fc5f052ebef1fbf193e8762ef509 | 46,664 |
from typing import Optional
from typing import Dict
from typing import Any
def bake(schema_name: str, config: Optional[Dict[str, Any]] = None) -> str:
"""
Links the directive to the appropriate schema and returns the SDL related
to the directive.
:param schema_name: schema name to link with
:param... | d2a58c0272ddeb6c39e7f1b78c56dd4c953ca9f0 | 46,665 |
def cents_to_ratio(c):
"""Cents to pitch ratio."""
return np.power(2, c/1200.0) | 018e7c962f77e3f25c1778fee2bdc5cb02adc27b | 46,666 |
def get_prev_frames(ind, path):
"""
for this index return the closest previous frame which is non none
:param ind: input index
:param path:
:return: frame and the count
"""
cur_ind = ind - 1
count = 1
while (path[cur_ind] is None and cur_ind >0):
count = count + 1
cur... | ddb48419e07a85c6c8d62eb4b034d6c5f2210a39 | 46,667 |
def test_metric_get(test_flask_client):
"""Tests the GET method"""
with mock.patch("bluebird.api.resources.metrics.utils", wraps=utils) as utils_patch:
sim_proxy_mock = mock.Mock()
utils_patch.sim_proxy.return_value = sim_proxy_mock
# Test no providers available
sim_proxy_moc... | 8d5a058b78ecb4d1e2703f16d99616fc87404bcb | 46,668 |
from typing import Dict
from typing import Any
async def create_remove_vote(res: Response, vote: VoteBaseModel) -> Dict[str, Any]:
"""create or remove a Vote from Vote table
Args:
vote (VoteBaseModel): vote to create or remove
Returns:
Dict[str, Any]: vote created
"""
response ... | 16c44d03a3ea9dc976091429b1d077cb043ef767 | 46,669 |
def delete_file(app_id, file_name, mode):
# type: (int, str, bool) -> bool
""" Call to delete_file.
:param app_id: Application identifier.
:param file_name: File name reference.
:param mode: Delete mode.
:return: The deletion result.
"""
return _COMPSs.delete_file(app_id, file_name, mod... | dac37c86de329ab39212589826c606dd0b6d210d | 46,670 |
def update_consumer_view(request):
"""
Updates a consuemr on ``POST`` request and returns the consumer update form for ``GET`` request.
.. http:get:: /consumer/update
Gets the consumer update form whose primary key matches the query parameter ``pk``.
**Example request**:... | d2a797fde068c7570611cac2d0943247b9c8726b | 46,671 |
def LastValueMinMaxQuantize(inputs,
min_var,
max_var,
bit_width,
is_training,
mode,
name_scope="LastValueMinMaxQuantize"):
"""Last value float scale q... | ae73bb701f3abfe6ef2a859880db60b5b39db63b | 46,672 |
def wikitext103_local_cluster4k():
"""Routing attention on sequence length 4k."""
hparams = wikitext103_local4k()
hparams.local_num_heads = 8
hparams.sparsity_cluster_num_heads = 8
hparams.sparsity_cluster_attention_window = 512
hparams.sparsity_cluster_size = 8
hparams.share_qk = True
return hparams | 3a256772c521f8ba17d4dd795d9d204d1fb7de46 | 46,674 |
def log10(pred, depth):
""" Mean log10 Error (LOG10) """
return np.absolute(np.log10(pred) - np.log10(depth)).mean() | 9a228d8179e3aa4530b70dac202ba57fc7549f3a | 46,675 |
def test_plan_built_on_method(hook):
"""
Test @sy.meth2plan and plan send / get / send
"""
hook.local_worker.is_client_worker = False
x11 = th.tensor([-1, 2.0]).tag("input_data")
x21 = th.tensor([-1, 2.0]).tag("input_data")
device_1 = sy.VirtualWorker(hook, id="device_1", data=(x11,))
... | 12ecce26ee149a690abcc8a7e41651e5d8273092 | 46,676 |
def get_proto_deserializer(proto_class):
"""
Return a proto deserializer that takes in a proto type to deserialize
the serialized msg stored in the RedisState proto
"""
def _deserialize_proto(serialized_rule):
proto_wrapper = RedisState()
proto_wrapper.ParseFromString(serialized_rule... | 4c509dccea826169c396510ef7f80cbf5fcf9b18 | 46,677 |
import requests
import json
import logging
def last_failed(url, job_type):
"""Return last failed job for a specified job type."""
# query
query = {
"query": {
"bool": {
"must": [
{
"terms": {
"s... | 567e5ef7afaa460e7fb91e09fa74d2d011cb2cdb | 46,678 |
def p2pkh_address_to_pubkey_hash(address):
"""
Takes a P2PKH address (starting with a 1, m or n symbol) and extracts its
HASH160 hash (used as a public key hash).
:see: https://en.bitcoin.it/wiki/List_of_address_prefixes
:param address: P2PKH public address
:returns: HASH160 hash of the ... | 95b6237b1c4a2492ab7283f104f2e6590b05eedc | 46,679 |
from typing import Optional
def get_dashboard(dashboard_id: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetDashboardResult:
"""
Resource schema for AWS::IoTSiteWise::Dashboard
:param str dashboard_id: The ID of the dashboard.
"""
__args__ = di... | bf5092d6c78edc6523c95ec1ffba79f86dec1924 | 46,680 |
def resize_intrinsics(intrinsics, target_size):
"""Transforms camera intrinsics when image is resized.
Args:
intrinsics: 1-d array containing w, h, fx, fy, x0, y0.
target_size: target size, a tuple of (height, width).
Returns:
A 1-d tensor containing the adjusted camera intrinsics.
"""
with tf.n... | 7216522da6a681d836171d16beb1507523bf4331 | 46,681 |
def fix_spaces_inside_quotes(text, quote='``'):
"""
>>> test = '''\
:meth:`update` accepte soit un autre objet dictionnaire ou un iterable de\
paires clé / valeur (comme tuples ou d'autres iterables de longueur deux).\
Si les arguments de mots clés sont spécifiés, le dictionnaire est alors mis\
... | cafb4dd7d15c4ab1a2cd252352d33b9aa20e4bca | 46,683 |
def toGoatLatin(S):
"""
:type S: str
:rtype: str
"""
count=1
sentences=S.split()
for i in range(len(sentences)):
if sentences[i][0].lower() in "aeiou":
sentences[i]+="ma"+count*"a"
else:
sentences[i]=sentences[i][1:]+sentences[i][0]+'ma'+count*"a"
count+=1
return " ".join(sentences) | ebc1e567dfa60436aea14412d7b347d8481f8b0a | 46,684 |
def __prepare_line(string, dir_source, replace_string):
"""
Prepare the line before it is being written into the content file
"""
if not replace_string == None:
string = string.replace(dir_source, replace_string)
return string | cbec6deab5c66960c5e8d57b52392e4ed3cf2b3d | 46,685 |
def create_adjacency_matrix(graph):
"""
Creating a sparse adjacency matrix.
:param graph: NetworkX object.
:return A: Adjacency matrix.
"""
index_1 = [edge[0] for edge in graph.edges()] + [edge[1] for edge in graph.edges()]
index_2 = [edge[1] for edge in graph.edges()] + [edge[0] for edge in... | 220a5465faa35c726008c7c4acf10c48bc44bb12 | 46,686 |
def count_trainable_parameters():
"""Counts the number of trainable parameters in the current default graph."""
tot_count = 0
for v in tf.trainable_variables():
v_count = 1
for d in v.get_shape():
v_count *= d.value
tot_count += v_count
return tot_count | 2e576db2be0815c770fdeea24bcf21d5d9353732 | 46,687 |
def create_diagram(start_from=None, kind="default", in_notebook=True):
"""Visually create a diagram.
Parameters
----------
start_from : list, optional
Starting coordinates (list of (x, y) tuples). By default uses a triangle.
kind : str
Can be one of "default", "x-marked".
in_not... | f99f4b7445c4d55f784892bc5294a29087be7b5c | 46,688 |
def extractsignalpdata(signalp_file_name,main_dic,translator_dic,n_termin_dict):
"""
This function reads an abridged signalp file, parses the signalp data and
adds the information in the (?) column to the main class.
"""
for line in open(signalp_file_name,'r'):
#Filter out title and s... | 2dc701d542c2a089fdf510de10885a89172fbd7b | 46,689 |
def mosaic_template(
endpoint: str, mapbox_access_token: str = "", mapbox_style="satellite"
) -> str:
"""Rio-viz viewer."""
return f"""<!DOCTYPE html>
<html>
<head>
<meta charset='utf-8' />
<title>Cogeo-Mosaic Viewer</title>
<meta name='viewport' content='initial-scale=1,maxi... | 9bb5e23caca6ce347ba56f3792ff8a130bbec423 | 46,690 |
def write_smiles(molecule, default_element='*', start=None):
"""
Creates a SMILES string describing `molecule` according to the OpenSMILES
standard.
Parameters
----------
molecule : nx.Graph
The molecule for which a SMILES string should be generated.
default_element : str
Th... | f1e13af728bdc8e1f13e6853d089ed3ce9b856e8 | 46,691 |
def find_closest_raster(return_period,aoi_col='AoI_RP{}y_unique',depth_col='RP{}_max_flood_depth'):
"""
Find the closest AoI and Flood raster column name for given return period
Arguments:
*return_period* (float): Return period of the flood for which to find the nearest inundation raster
*a... | 177041afc9a52d4942ab4095b7383cfc8e17652b | 46,692 |
def svn_diff_fns_invoke_datasource_get_next_token(*args):
"""svn_diff_fns_invoke_datasource_get_next_token(svn_diff_fns_t _obj, void diff_baton, svn_diff_datasource_e datasource) -> svn_error_t"""
return _diff.svn_diff_fns_invoke_datasource_get_next_token(*args) | 9d9b0dd2ac2214c05cc7af5e1fca5f804b1feb5b | 46,693 |
def _is_bn_diff_doctypes(dyad):
"""Check if a dyad is between two different doctypes.
Args:
dyad (tuple): two-item tuple where each item is a dict which represents a document
Returns:
ind (bool): True if the dyad is between two different doctypes
"""
if dyad[0]["doctype"] != dyad[... | 2480cbca808164b2fec14fd13808cf5ebfb0dcc3 | 46,694 |
import operator
def selectcontains(table, field, value, complement=False):
"""Select rows where the given field contains the given value."""
return selectop(table, field, value, operator.contains,
complement=complement) | 29753f270791a3187bf0a2a87fc5ec6b379178ed | 46,695 |
def with_path_to(q, value, info, union=False, name='with_path_to'):
"""This will traverse any (any meaning any paths specified in the path
generation heuristic which prunes some redundant/wandering paths)
from the source entity to the given target type where it will
apply a given query.
This filter... | 68c9ceddf0a9b2bcc5d39262f5f7d94deb47e4db | 46,696 |
from typing import Dict
from typing import List
import urllib
from bs4 import BeautifulSoup
import logging
def get_links(entry: Dict, html_data: Text) -> List[urllib.parse.ParseResult]:
"""Extract any links from the html"""
links = []
soup = BeautifulSoup(html_data, "html.parser")
if soup:
li... | b3c1fc02c145387b3d4e639ff9fa0ff594953e55 | 46,697 |
def conjgrad (A, b, x = None, iterations = 10**6, epsilon = 10**(-10)):
"""
Méthode du gradient conjugué.
-----------------------------
Entrée:
A matrice symétrique définie positive.
b vecteur colonne.
(optional) x vecteur initial de la suite.
... | 62708a3d3dfd8afc20cf1b43fcff92614b0c3392 | 46,698 |
from datetime import datetime
import binascii
def is_valid(token):
"""Checks if the token is valid.
Args:
token (str): Token
Returns:
Boolean: True or false
"""
if len(token) < 64:
return False
now = datetime.now().timestamp()
time = token[22:][:20]
decode_tim... | ea1b28d2a04f3d72a0388c41feeb2bd764a78239 | 46,701 |
def shared_dataset(filename):
"""Returns the training-, validation- and test-datasets as shared variables"""
train_set, valid_set, test_set = load_dataset(filename)
train_x, train_y = shared_variables(train_set, 'Training')
valid_x, valid_y = shared_variables(valid_set, 'Validation')
test_x, test_y... | 71ff6a10845720f0eb2bb6f7f9035574cb52970d | 46,702 |
def _stats_print(good_noise, good_gains, good_fit, test_chans):
"""Generate a simple set of statistics for the test
and print them to screen.
"""
print("\nFilter statistics:")
good_chans = [1] * len(test_chans)
Nact = len(test_chans) # Number of active channels
if good_noise is not None:
... | 31044ffd6966a0e7d910bcafa92616de36ce4e81 | 46,703 |
def text():
"""make text files"""
return build('text', 'The text files are in {}.') | b066b813722be90c69eae68972cf33475c5f0023 | 46,704 |
import requests
def upload2ipfs(file_path: str) -> str:
"""Upload to ipfs using local port.
IPFS node must be running locally. Run:
$ ipfs daemon
Args:
nft_path (str): path to metadata file
"""
with open(file_path, "rb") as f:
nft_binary = f.read()
ipfs_endpoint = "http://... | 4fdb53d4d6d61b1784673be6d84cb7ba41fc84a5 | 46,705 |
def rotateImage(imgdata, org_corners):
"""
"""
rotation = calculateRotation(org_corners.ul, org_corners.ur)
rot_img = skimage.transform.rotate(imgdata, rotation, resize = True, preserve_range = True)
return rot_img | c4649b964a99345b62b4b53184efe5757639f0e2 | 46,706 |
def mean_absolute_scaled_error(y_true: ArrayLike, y_pred: ArrayLike) -> float:
"""Compute the mean absolute scaled error (MASE).
MASE is computed by comparing mean absolute error of the predictions to
the mean absolute error obtained from a lag-1 forecast.
Args:
y_true: the actual values.
... | 7931d81f952e692f1b14f578ee93182b3289074d | 46,707 |
def GetCloudBasePath():
"""Returns the folder within the Makani bucket where all databases live."""
return 'gs://gcp-public-data-makani-deps/deps/turbsim_databases' | 40091d491fdc3960cc5aa08e0ca58ae0cf2009aa | 46,708 |
import json
def create_entity(station: WeatherStationTuple) -> dict:
""" Conversion from input data to desired properties and types """
entity = Entity()
entity.provider = 'bom'
entity.country = 'Australia'
entity.country_code = 'AU'
entity.state = station.state
entity.site = station.site... | 2e6398490afdee43a5d8d43c58634ffdff7bc3dd | 46,709 |
def line(char='-', length=48):
"""Generates a string of characters with a certain length"""
return ''.join([char for _ in range(length)]) | 32de8abb95ab7e73912e2b37f0996361ed181c5b | 46,710 |
import collections
def dict_update(d, u):
"""Recursive update dictionary"""
for k, v in u.items():
if isinstance(v, collections.Mapping):
d[k] = dict_update(d.get(k, {}), v)
else:
d[k] = v
return d | bf49b0e4a8f35595a2258aaadcad231d8b9325da | 46,711 |
def _handle_tracking(request, response):
"""Handles the share tracking logic so that users get their number of shares increased
when someone downloads Firefox mobile via their user page."""
if not _has_parent_cookie(request):
parent_username = _add_share_from_cookies(request)
# Set a 'par... | f491e44253face9148aaf4f4e09cb122c4b495b6 | 46,712 |
def prompt_yn(msg, default=None):
"""
Prompts the user for a y/n response.
default param should be either 'y' or 'n'
Returns True if 'Y' and False if 'N'
"""
if default is True:
default = 'y'
elif default is False:
default = 'n'
if default == 'y' or default is True:
... | f5df7d5bf32153dd1a0e34b26997aabd683066f8 | 46,713 |
def noise_for_example(x, extent=1000, intensity=0.1, rng=None, **kwargs):
"""
Add noise to x. Just for demonstration.
Arguments:
extent -- number of points to add noise at
intensity -- scale parameter of half-normal distribution; samples
from this distribution will be added at each nois... | 55a76ea075f6f36d874293ee8aacbd1419fd1e32 | 46,714 |
def datasets_loader(conf, train=True, dev=True, test=True):
"""
simple wrapper for unified interface of datasets loaders
"""
fmt = conf.pop("fmt")
if fmt == "kaldi_ra":
return kaldi_ra_datasets_loader(conf, train, dev, test)
else:
raise ValueError("dataset format %s not supported... | d82f097e00cffc31ee53ac1a57635a1fcc871990 | 46,717 |
import json
def remove_existing_datasets(viable_datasets, connection):
"""Remove the viable datasets that are already existing datasets."""
for dataset_type in viable_datasets:
for container, datasets in viable_datasets[dataset_type].items():
actually_viable_datasets = []
for ... | 889a87d144c795b1bfe40aaad92ca1b36c64b3b3 | 46,718 |
import logging
def group_by_size(input_tensors, bytes_per_pack):
"""Groups `input_tensors` into chunks of `bytes_per_pack`.
The method preserves the original order of `input_tensors`. The grouping is
best effort, each pack could have more or less bytes than `bytes_per_pack`.
It only groups values with known ... | 9ab5805898678b1541f116e5ef5ae1b9a1c42791 | 46,719 |
def np_emd_loss(y_true, y_pred, reduction_axis=None, num_bins=327, **kwargs):
"""Earth Mover Distance between two waveforms
Parameters
----------
y_true : np.ndarray
A tensorflow tensor defining the true waveform
shape: [batch_size, num_bins]
y_pred : np.ndarray
A tensorflow... | d5c70b35d466d8c62efb31c91cef87da5eebd076 | 46,720 |
def adapters(text):
"""
Parse lines of text into a list of adapters (represented by their joltage),
supplemented by the outlet (0) and your device (maximum + 3).
"""
adapters = list(sorted(map(int, text.splitlines())))
adapters = [0] + adapters + [max(adapters) + 3]
return adapters | cb5aa44963506e8d0ea6aa0aeb89d094bfbb0bc8 | 46,721 |
def assign_bonds_to_groups(tors, group):
"""
|
**Description:** Make a group for each torsion bond
and keep track of how many members
Finally it returns the biggest group.
**Input:**
- Tors: atoms with torsions
- Group: Atoms grouped by proximity
**Output:**
- output: li... | 8147c016efe435f46b587bc86e6fab713375bb70 | 46,722 |
def _build_generator_map():
"""Build a map of sdtype to data generator.
Output:
dict:
A mapping of sdtype (str) to a list of data
generators (rdt.tests.datasets.BaseDatasetGenerator).
"""
generators = defaultdict(list)
for generator in BaseDatasetGenerator.get_subcl... | 4660f8b84f1a048942e519d188b17bac10903b1f | 46,723 |
import re
def get_ignore_unknown_patterns():
"""
Fetch the value of the setting that tells us what unknown overrides we
should ignore in reports. The regular expressions from the settings file
(if any) are compiled in the returned list.
When the setting is a boolean, the result is either an empty... | 5437159c9bddbc80585e31156d0740108df2dcca | 46,725 |
def test_dal_method_middleware():
"""
Verify that when calling a method on a service off the DAL,
the method middlewares run, in the correct order and run
before the method itself is called.
We deliberately do not use the DalMethodResolverMiddleware here,
because we are testing middleware call... | 71f43002001b5c4bb2b43f72ac29ab4bae9e6159 | 46,727 |
def chain_functions(fun_first: tp.Callable[..., tp.Union[tp.Tuple[tp.Tuple, tp.Dict],
tp.Dict, tp.Tuple]]) -> tp.Callable:
"""
A decorator to chain function calls.
This function is expected to return:
* a 2-tuple [tp.Tuple, tp.Dict] - args and k... | e78f42d30fb788751703f1b56bafd485b27c1a0e | 46,728 |
from typing import Union
import types
from typing import List
from typing import Tuple
from typing import Set
def find_variables(
expr: Union[types.Constraint, List[types.Constraint], Tuple[types.Constraint]]
) -> Set[core.Symbol]:
"""Find variables in constraints."""
if not isinstance(expr, (list, tuple)):
... | d9b737260b1c2b5d25f6718530ed74245c76abfd | 46,729 |
def _number_of_neighbors(i, j, height, width, state):
"""
Counts the number of LIVE neighbors of the cell in position (i, j).
:param i: Row of the cell.
:param j: Column of the cell.
:param height: Height of the input state.
:param width: Width of the input state.
:param state: A game state... | cb88e81fb7124ef6c97de75cfecef5b11767da14 | 46,730 |
def _format_cpu_memory(container_group):
"""Format CPU and memory. """
containers = container_group.get('containers')
if containers is not None and containers:
total_cpu = 0
total_memory = 0
for container in containers:
resources = container.get('resources')
i... | 1e1db12afd45a6d0634a6d9f701f3c3bb7bc9570 | 46,731 |
def create_category(name):
"""
Create a new category
:param name:
:return object:
"""
category = Category(name=name)
session.add(category)
session.commit()
return category | 512092a2b3c3c9fd4a912f99dbfe35a8645d228e | 46,732 |
def logpost_negb(state,params):
"""
Compute log-posterior density values; this function assumes
the likelihood is a product of negative-binomial distributions
Parameters
----------
state: python list or numpy array
model parameters
params: dictionary
detailed settings for... | 0b88b2f39f70d7cd07f8cfbd9a8434f56ba306ad | 46,733 |
import functools
def matcher(callable_or_names, names=None):
"""
Implicitly registers it with function's __name__, "be_a_dog":
@matcher
def be_a_dog(x):
return type(x) == dog
Explicitly registers it with names "be_a_dog" and "be_canine"
@matcher("be_a_dog, be_canine")
def whatev... | 6e79149c45ba32576d9fa7cde373d14279c401e9 | 46,735 |
def update_tree(
tree: EmptyTree, oid: str, current_user: User = Depends(get_current_active_user)
):
"""
Update tree DB entry
"""
print(tree)
try:
selected_tree = TreeDB.objects.get(id=oid)
selected_tree.species = tree.species if tree.species else selected_tree.species
s... | 49ac41202d2b6471574a55cacfcf746b646437b3 | 46,736 |
def get_queue_jobs(queue_name):
"""Get the jobs by status of a Queue.
Args:
queue_name (str): The RQ Queue name
Returns:
dict: Number of jobs by job status
Raises:
redis.exceptions.RedisError: On Redis connection errors
"""
queue = Queue(queue_name)
return {
... | a5ba497545955ad5bb42406cf289d69f05b1101a | 46,737 |
def update_lengths(lengths, eoses, idx):
"""Update the length of a generated tensor based on the first EOS found.
This is useful for a decoding situation where tokens after an EOS
can be something other than EOS. This also makes sure that a second
generated EOS doesn't effect the lengths.
:param l... | bad4dce46e498da09400673abacebdba8db5ddae | 46,738 |
def delete_widget_config(id_):
"""Deletes a widget
:param id: ID of the widget to delete
:type id: str
:rtype: tuple
"""
widget_config = WidgetConfig.query.get(id_)
if not widget_config:
return "Not Found", 404
else:
session.delete(widget_config)
session.commit(... | 74e9e1568cbbcfe825dc936699682db270aa0125 | 46,739 |
def detail_view(request):
"""
Directs user to the detail template
"""
try:
symbol = request.matchdict['symbol']
except KeyError:
return HTTPNotFound()
try:
query = request.dbsession(Account)
stock_detail = query.filter(Account.username == request.authenticated_us... | aa45381bce120007a6fd957b0d3c433ec0fa3303 | 46,740 |
def is_right_censored(lc, frange):
""" Returns true if the light curve is cutoff on the right. """
return len(lc['t0'])-1 in frange | de2e81605db2dc2a5f073d8400e2e8ee1b46f199 | 46,741 |
def neural_net_learning_rate_input():
"""
Return a Tensor for the learning rate
"""
return tf.placeholder(tf.float64, name="learning_rate") | 3d7e21cafd617b69aafa439c238f9d16c0eb28b4 | 46,742 |
def decode_csr(b64der):
"""
Decode JOSE Base-64 DER-encoded CSR.
:param str b64der: The encoded CSR.
:rtype: `cryptography.x509.CertificateSigningRequest`
:return: The decoded CSR.
"""
try:
return x509.load_der_x509_csr(
jose.decode_b64jose(b64der), default_backend())
... | 0eb7dd2acd8cd8a210969e0ea1d2e99ecca07a97 | 46,743 |
def retrieve_span(task, task_id):
"""Helper to retrieve an active `Span` stored in a `Task`
instance
"""
weak_dict = getattr(task, CTX_KEY, None)
if weak_dict is None:
return
else:
return weak_dict.get(task_id) | 74d003e9b2a019a8b0b1527952dabcb8a21f6e2b | 46,744 |
def check_data(func):
"""Decorator function for checking possible exceptions during extraction.
Args:
func (obj): function used in try-except block
Except:
(str) : in case of exception assigns '-' for the missing data.
"""
def inner(line):
try:
return func(line)... | b9dad9ff8adbee9f8307c4c61fc2d5e1918092e2 | 46,745 |
def fscale(ns, si=1, one_sided=False):
"""
numpy.fft.fftfreq returns Nyquist as a negative frequency so we propose this instead
:param ns: number of samples
:param si: sampling interval in seconds
:param one_sided: if True, returns only positive frequencies
:return: fscale: numpy vector contain... | f6cf820c184651396c3fc61a366391c9d03f086b | 46,746 |
def get_features_from_files(
data_dir,
features_ext='.proc.c3d-avg.npy',
test_split=[],
classes=None,
max_elements=13320):
"""
Creates and executes mPyPl pipe to load feature vectors from serialized files and returns a preprocessed
data stream that can be further used with respect to... | f53f0781a6108e8e31ba75613c007368b095fdfb | 46,747 |
import json
import hashlib
def crypto_hash(*args):
"""
Return a SHA-256 hash of the given arguments
"""
stringified_args = sorted(map(lambda x: json.dumps(x), args))
joined_data = "".join(stringified_args)
return hashlib.sha256(joined_data.encode("utf-8")).hexdigest() | 3c4329a6e99826a15e52e2921040045697ce5aa0 | 46,748 |
def vectorized(csm, e, h, r0, rm, kj):
""" Uses Numpys fast array operations, distributed via the mkl-package.
Those oparations are already optimized and use all available physical cores.
"""
nFreqs = csm.shape[0]
nGridPoints = r0.shape[0]
beamformOutput = np.zeros((nFreqs, nGridPoints), np.comp... | 15c2fb6a9f7f8551314d0a0e9c219308dc7b2741 | 46,749 |
def is_empty_line(line: str) -> bool:
"""Checks whether a line is empty."""
return line.strip("\n").strip("\t").strip() == "" | ad58cc78e5f25353419682343c34c21e2679304d | 46,750 |
def to_host_list(value):
"""Space separated list of FQDNs."""
return value.split() | 85740e6e90096d5711022a7ae18b919673899b36 | 46,751 |
import click
def drop_prediction_column(data_path, group_name, column_name, yes=True):
"""
Deletes prediction columns in a h5py file if the columns exist.
Including 'mean' and 'std' columns.
"""
n_del = 0
with h5py.File(data_path, "r+") as f:
if group_name not in f.keys():
... | 9ac7e06ddcf71af87b383ecefe5f3aac1a0e2159 | 46,752 |
def create_indep_noise_weight_matrix(Nbm, Knoise, gamma, g, w):
"""create a weight matrix for Nbm * Knoise sources projecting to Nbm
targets with a fixed indegree of Knoise. no shared inputs are
allowed, hence each target receives uncorrelated input of the
sources are uncorrelated.
"""
Nnoise ... | 4760fcf51d9418243df7ecb9027d81b77dd85a00 | 46,753 |
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